Bacterial community composition of the gut microbiota of Cylindroiulus fulviceps (diplopoda) as revealed by molecular fingerprinting and cloning.

Bacterial clone libraries of the gut microbiota of nurtured and starved Cylindroiulus fulviceps specimens displayed the predominance of the phyla Bacteroidetes (55 and 37 %, respectively) and Proteobacteria (40 and 35 %, respectively) and a high similarity to bacteria previously detected in the intestinal tract of termites and beetles, which are known to harbor symbiotic bacteria essential for digestive activity. Bacterial isolates were dominated by Proteobacteria (74 %), followed by members of the phyla Actinobacteria, Firmicutes and Bacteroidetes. PCR-DGGE fingerprints of the gut samples showed that intestinal bacteria were affected by starvation, although the change was not significant.

Fallopian tube cancer associated with paraneoplastic dermatomyositis -- asymptomatic multivisceral exacerbated dermatomyositis mimicking recurrent widespread malignant disease: case report.

OBJECTIVE: To report an uncommon case of a recurrent episode of primarily paraneoplastic dermatomyositis which was completely disconnected from the initially triggering malignancy and manifested as a silent pure multivisceral exacerbation. CASE: A 70-year-old woman presented with a pure multivisceral episode of dermatomyositis without characteristic musculo-cutaneous symptoms one year after successful treatment of fallopian tube carcinoma with complete resolvement of a concomittant paraneoplastic dermatomyositis. The uncommon manifestation of recurrent dermatomyositis involving the lungs, spleen and liver, both adrenal glands and abdominal lymph nodes, mimicked a highly disseminated recurrence of the fallopian tube cancer. Physicians participating in the interdisciplinary tumor board were misled to opt for reinductive chemotherapy. Only histologic diagnosis obtained from multiple biopsies uncovered the inflammatory nature of the disease and spared the patient unneeded chemotherapy. CONCLUSION: Asymptomatic multivisceral dermatomyositis may mimic metastatic spread of the initially underlying malignancy and may misdirect therapeutic strategies towards inadequate antineoplastic treatment.

Application of denaturing gradient gel electrophoresis for analysing the gut microflora of Lumbricus rubellus Hoffmeister under different feeding conditions.

The earthworm, Lumbricus rubellus, plays an essential role in soil ecosystems as it affects organic matter decomposition and nutrient cycling. By ingesting a mixture of organic and mineral material, a variety of bacteria and fungi are carried to the intestinal tract of the earthworm. To get a better understanding of the interactions between L. rubellus and the microorganisms ingested, this study tried to reveal if the diet affects the composition of the gut microflora of L. rubellus or if its intestinal tract hosts an indigenous, species-specific microbiota. A feeding experiment with L. rubellus was set up; individuals were collected in the field, transferred to a climate chamber and fed with food sources of different quality (dwarf shrub litter, grass litter or horse dung) for six weeks. DNA was extracted from the guts of the earthworms, as well as from the food sources and the surrounding soil, and further analysed by a molecular fingerprinting method, PCR-DGGE (Polymerase Chain Reaction -- Denaturing Gradient Gel Electrophoresis). We were able to demonstrate that the gut microbiota was strongly influenced by the food source ingested and was considerably different to that of the surrounding soil. Sequencing of dominant bands of the bacterial DGGE fingerprints revealed a strong occurrence of y-Proteobacteria in all gut samples, independent of the food source. A specific microflora in the intestinal tract of L. rubellus, robust against diet changes, could not be found.

Design and implementation of a random neural network routing engine.

Random neural network (RNN) is an analytically tractable spiked neural network model that has been implemented in software for a wide range of applications for over a decade. This paper presents the hardware implementation of the RNN model. Recently, cognitive packet networks (CPN) is proposed as an alternative packet network architecture where there is no routing table, instead the RNN based reinforcement learning is used to route packets. Particularly, we describe implementation details for the RNN based routing engine of a CPN network processor chip: the smart packet processor (SPP). The SPP is a dual port device that stores, modifies, and interprets the defining characteristics of multiple RNN models. In addition to hardware design improvements over the software implementation such as the dual access memory, output calculation step, and reduced output calculation module, this paper introduces a major modification to the reinforcement learning algorithm used in the original CPN specification such that the number of weight terms are reduced from 2n/sup 2/ to 2n. This not only yields significant memory savings, but it also simplifies the calculations for the steady state probabilities (neuron outputs in RNN). Simulations have been conducted to confirm the proper functionality for the isolated SPP design as well as for the multiple SPP's in a networked environment.